Skills
What our Vertex AI developers know
We put forward developers with production Vertex AI experience, and you interview them before they join your team.
- Vertex AI and Gemini on Google Cloud
- Grounded search over BigQuery and Cloud Storage
- Cloud Run and Cloud Functions services
- IAM, service accounts and VPC controls
- Pipelines and scheduled jobs
- Monitoring with Cloud Logging
Roles
Who you can hire
GCP AI engineer
Builds and deploys AI services inside your Google Cloud project.
Data and AI developer
Connects BigQuery and storage to models for search, reporting and extraction.
Platform developer
Sets up environments, permissions and deployment pipelines for AI workloads.
Engagement
Ways to work with us
Dedicated developer
A full-time developer on your project: 160 hours a month, your tools, your standups.
Part-time or hourly
Hours when you need them, for a defined backlog or ongoing improvements, with every billed hour tracked in Hubstaff.
A small team
Developers plus a lead who plans the work, reviews code and sends daily or weekly reports by email.
Hiring terms
Low risk to start, easy to change
2-week trial
Start with a two-week trial before you commit.
Free replacement
If a developer isn’t the right fit, we replace them at no cost.
No minimum term
No long-term contract and no minimum hours. Scale up, down or stop when you need to.
You own the code
The code and IP are yours, and we sign an NDA before we see your codebase.
Full-time Widle employees
Every developer is on our team in Ahmedabad. No freelancers, no subcontractors.
Start in 1–2 weeks
A developer usually joins your team within one to two weeks of your enquiry.
Junior to lead
Junior, mid-level and senior developers, or a lead who plans the work and reviews code.
Hours that fit yours
Our day runs 9:00 am–7:00 pm IST; for US teams we shift hours to overlap with yours.
How it works
Hire Vertex AI developers in four steps
- 01
Enquiry
Share your requirements: stack, scope, time zone and how many developers you need.
- 02
Shortlist profiles
We share the profiles of suitable developers for you to shortlist.
- 03
Interview
Your team interviews the shortlisted candidates and picks who to work with.
- 04
Add to team
The developer joins your team and starts on your project, with reporting from day one.
Vetting
How we vet Vertex AI developers
A few of the questions we ask, and what a good answer tells us. Use them in your own interview too.
- Q1
How would you give a service only the permissions it needs?
Checks IAM and least-privilege practice.
- Q2
How do you ground answers in BigQuery data?
Tests retrieval design on Google Cloud.
- Q3
How do you deploy changes safely?
Looks for staging, rollbacks and infrastructure as code.
- Q4
What would you monitor after launch?
Checks logging, error rates and cost.
Vertex AI at Widle
What we build with Vertex AI
AI Full-Stack Development
AI products that hold up with real users: SaaS platforms, copilots and AI features inside your app, with the unglamorous parts (auth, billing, testing and monitoring) done properly.
Learn more →AI Agents & LLM Apps
Assistants that answer from your documents, use your tools and hand over to a person when they should, tested before they meet a customer.
Learn more →ETL & Data Pipelines
Get data out of every app, clean it and land it where your reports and AI can use it. Scheduled, logged and checked.
Learn more →Hiring Vertex AI developers: FAQs
Will the work stay inside our GCP project?
Yes. Developers work in your project with the access you grant.
Do they also know BigQuery?
Yes. Most Vertex AI work involves BigQuery and Cloud Storage.
Can we start with one developer and add more?
Yes. You can scale from a single developer to a small team.